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Creating a Multiply Imputed Value Set for the EQ-5D-5L in Canada: State-Level Misspecification Terms Are Needed to Characterize Parameter Uncertainty Correctly.

Teresa C O TsuiKelvin Kar-Wing ChanFeng XieEleanor M Pullenayegum
Published in: Medical decision making : an international journal of the Society for Medical Decision Making (2024)
Value sets for health state utility instruments are estimated subject to parameter uncertainty; this parameter uncertainty may exceed the minimum important difference of the instrument, yet it is not fully captured using current methods.This study creates the first multiply imputed value set for a multiattribute utility instrument, the EQ-5D-5L, to fully capture this parameter uncertainty.We apply the multiply imputed value set to 2 data sets from 1) the Canadian general public and 2) women with invasive breast cancer.Scoring the EQ-5D-5L using a multiply imputed value set led to wider standard error estimates, suggesting that the current practice of ignoring parameter uncertainty in the value set leads to falsely low standard errors.Our work will be of interest to methodologists and developers of the EQ-5D-5L and users of the EQ-5D-5L, such as health economists, researchers, and policy makers.
Keyphrases
  • healthcare
  • public health
  • mental health
  • health information
  • primary care
  • emergency department
  • big data
  • risk assessment
  • electronic health record
  • adverse drug
  • quality improvement
  • artificial intelligence
  • human health